Lecture des données :
library(tidyverse)
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flux <- read_csv("../data/obs_artif_conso_com_2009_2020_V2.csv", na = c("", "NULL"))
## Rows: 34938 Columns: 85
## -- Column specification --------------------------------------------------------
## Delimiter: ","
## chr (9): idcom, idcomtxt, idreg, idregtxt, iddep, iddeptxt, epci20txt, aav2...
## dbl (76): epci20, cateaav2020, naf09art10, art09act10, art09hab10, art09mix1...
##
## i Use `spec()` to retrieve the full column specification for this data.
## i Specify the column types or set `show_col_types = FALSE` to quiet this message.
# Palette
colorBlue <- hcl(h = 220, c = 50, l = 80, fixup = TRUE)
colorRed <- hcl(h = 4, c = 50, l = 80, fixup = TRUE)
colorMagenta <- hcl(h = 300, c = 50, l = 80, fixup = TRUE)
colorGrey <- hcl(h = 0, c = 0, l = 80, fixup = TRUE)
myPalette <- c("blue" = colorBlue,
"red" = colorRed,
"magenta" = colorMagenta,
"grey" = colorGrey)
library(plotly)
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##
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## last_plot
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## filter
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## layout
makeTreemap <- function(flux, codeInsee) {
df <- flux %>% filter(idcom == codeInsee)
df <- df %>% gather("variable",
"value",
c("arthab0920", "artact0920", "artmix0920", "artinc0920"))
df$variable <- case_when(
df$variable == "arthab0920" ~ "Habitat",
df$variable == "artact0920" ~ "Activité",
df$variable == "artmix0920" ~ "Mixte",
df$variable == "artinc0920" ~ "NC"
)
# Par. treemap
labels = df$variable
parents = rep("", nrow(df))
values = df$value
fig <- plot_ly(
type="treemap",
labels=labels,
parents=parents,
values=values,
marker=list(colors = myPalette))
fig
}
Faisons la treemap de la commune d’Aix en Provence :
flux %>% makeTreemap("13001")
Faisons la treemap sur Toulon :
flux %>% makeTreemap("83137")